Gene annotation and network inference by phylogenetic profiling

Background: Phylogenetic analysis is emerging as one of the most informative computational methods for the annotation of genes and identification of evolutionary modules of functionally related genes. The effectiveness with which phylogenetic profiles can be utilized to assign genes to pathways depends on an appropriate measure of correlation between gene profiles, and an effective decision rule to use the correlate. Current methods, though useful, perform at a level well below what is possible, largely because performance of the latter deteriorates rapidly as coverage increases. Results: We introduce, test and apply a new decision rule, correlation enrichment (CE), for assigning genes to functional categories at various levels of resolution. Among the results are: (1) CE performs better than standard guilt by association (SGA, assignment to a functional category when a simple correlate exceeds a pre-specified threshold) irrespective of the number of genes assigned (i.e. coverage); im...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Jie Wu, Zhenjun Hu, Charles DeLisi
• Keywords: BMCBI 2006, Decision Rule, Effective Decision Rule, Informative Computational Methods